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author | nunzip <np.scarh@gmail.com> | 2019-03-08 18:30:14 +0000 |
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committer | nunzip <np.scarh@gmail.com> | 2019-03-08 18:30:14 +0000 |
commit | 97cc07ebc57a813f1fd4b32f314f455c033ab55a (patch) | |
tree | c0c1fc60d55baf0bfc3b62962f714290ea7bb321 /lenet.py | |
parent | 240be62b504dbdcb0cadcaf313d111eefe9ceea0 (diff) | |
download | e4-gan-97cc07ebc57a813f1fd4b32f314f455c033ab55a.tar.gz e4-gan-97cc07ebc57a813f1fd4b32f314f455c033ab55a.tar.bz2 e4-gan-97cc07ebc57a813f1fd4b32f314f455c033ab55a.zip |
Remove get_lenet_pen
Diffstat (limited to 'lenet.py')
-rw-r--r-- | lenet.py | 13 |
1 files changed, 0 insertions, 13 deletions
@@ -83,19 +83,6 @@ def get_lenet_icp(shape): model.add(Dense(units=10, activation = 'relu')) return model -def get_lenet_pen(shape): - model = keras.Sequential() - model.add(Conv2D(filters=6, kernel_size=(3, 3), activation='relu', input_shape=(32,32,1))) - model.add(AveragePooling2D()) - - model.add(Conv2D(filters=16, kernel_size=(3, 3), activation='relu')) - model.add(AveragePooling2D()) - model.add(Flatten()) - - model.add(Dense(units=120, activation='relu')) - model.add(Dense(units=84, activation='relu')) - return model - def plot_history(history, metric = None): # Plots the loss history of training and validation (if existing) # and a given metric |